Horizontally acquired genetic elements frequently provide bacteria with new and potentially problematic capabilities, such as resistance to antibiotics or acquisition of virulence factors. One crucial, but often overlooked, factor that must play a role in the behavior of such insertions is how the location of a new piece of genetic information affects its expression. Several recent studies have shown that genomic location may alter gene expression, at least in part due to the presence of transcriptionally silent regions in the chromosome of high protein occupancy, although to date only on the order of a few dozen different sites have been considered. Nevertheless, these findings raise the questions: To what extent is gene expression regulated through chromosome structure in bacteria? And what role does such regulation play in bacterial evolution and horizontal gene transfer? To analyze the effect of chromosomal position on gene expression at a high resolution, we will apply a recently developed multiplex strategy to construct and analyze several thousand genome-integrated reporters in a single mixed population of E. coli. RNA produced from the transcription of an integrated reporter will carry a barcode sequence that specifies a unique integration site, in addition to coding for a fluorescent protein. By sequencing RNA barcodes per corresponding DNA barcode, we will generate a normalized high-resolution map of reporter transcription variation across the bacterial genome. We will use flow cytometry-sorted subsamples of the same population to determine variations in the shapes of the distribution of protein levels present for reporter integrations at different locations. The ability to determine both the transcriptional and translational variations attributable solely to genomic location will provide powerful new insight into the organization of bacterial genomes, and in particular, into the manner in which horizontally acquired elements such as virulence and antibiotic resistance determinants are integrated into existing cellular networks. In addition, the developed method for profiling location-based expression variation will be readily applicable to other strains and species, providing a powerful new tool for investigating similar questions in other organisms.